Background
Notes and format last updated May 7, 2020
Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.
- This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
- The table of contents above summarizes the major sections and can be used to jump to those sections.
- Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
- If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
- More detailed descriptions and context can be found in each section.
Growth rates
Heat maps
- The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
- The first plot compares growth rate for total cases; the second, growth rate for total deaths.
- The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
- The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
- You can use the plots to track each geography over time and to compare the geographies to one another.
- You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.


Case growth rates
- This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
- There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
- Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
- Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
- For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
- For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.
U.S.

Death growth rates
- This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
- There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
- Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
- Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
- For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
- For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.
U.S.

By population rankings
This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.
States
- This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
- For each metric, in addition to the tables, the trends for the top states are plotted over time.
- We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.
Total confirmed cases
Table of total confirmed cases per million residents (all 50 states)
|
Ranking
|
State
|
Cases Per Million
|
|
1
|
Louisiana
|
23,668
|
|
2
|
Arizona
|
22,520
|
|
3
|
New York
|
21,438
|
|
4
|
New Jersey
|
20,460
|
|
5
|
Florida
|
20,148
|
|
6
|
Mississippi
|
17,793
|
|
7
|
Rhode Island
|
17,477
|
|
8
|
Massachusetts
|
16,819
|
|
9
|
District of Columbia
|
16,802
|
|
10
|
Alabama
|
16,543
|
|
11
|
South Carolina
|
16,007
|
|
12
|
Delaware
|
14,794
|
|
13
|
Georgia
|
14,684
|
|
14
|
Nevada
|
14,246
|
|
15
|
Maryland
|
14,131
|
|
16
|
Texas
|
13,874
|
|
17
|
Illinois
|
13,766
|
|
18
|
Tennessee
|
13,745
|
|
19
|
Connecticut
|
13,738
|
|
20
|
Iowa
|
13,532
|
|
21
|
Arkansas
|
13,071
|
|
22
|
Nebraska
|
12,871
|
|
23
|
Utah
|
11,989
|
|
24
|
California
|
11,821
|
|
25
|
North Carolina
|
10,935
|
|
26
|
Idaho
|
10,540
|
|
27
|
Virginia
|
10,083
|
|
28
|
Indiana
|
9,568
|
|
29
|
South Dakota
|
9,544
|
|
30
|
New Mexico
|
9,300
|
|
31
|
Minnesota
|
9,192
|
|
32
|
Wisconsin
|
9,158
|
|
33
|
Kansas
|
9,075
|
|
34
|
Pennsylvania
|
8,826
|
|
35
|
Michigan
|
8,744
|
|
36
|
Oklahoma
|
8,220
|
|
37
|
North Dakota
|
7,860
|
|
38
|
Colorado
|
7,766
|
|
39
|
Missouri
|
7,301
|
|
40
|
Washington
|
7,294
|
|
41
|
Ohio
|
7,286
|
|
42
|
Kentucky
|
6,323
|
|
43
|
Puerto Rico
|
4,831
|
|
44
|
New Hampshire
|
4,737
|
|
45
|
Alaska
|
4,379
|
|
46
|
Wyoming
|
4,354
|
|
47
|
Oregon
|
4,059
|
|
48
|
West Virginia
|
3,378
|
|
49
|
Montana
|
3,186
|
|
50
|
Maine
|
2,850
|
|
51
|
Vermont
|
2,246
|
|
52
|
Hawaii
|
1,192
|

New confirmed cases
Table of new cases per million residents: rolling 3-day average (all 50 states)
|
Ranking
|
State
|
New Cases Per Million
|
|
1
|
Florida
|
472
|
|
2
|
Louisiana
|
443
|
|
3
|
Mississippi
|
368
|
|
4
|
Tennessee
|
351
|
|
5
|
Alabama
|
347
|
|
6
|
Arizona
|
344
|
|
7
|
Nevada
|
310
|
|
8
|
Oklahoma
|
287
|
|
9
|
Idaho
|
265
|
|
10
|
Georgia
|
256
|
|
11
|
South Carolina
|
246
|
|
12
|
Arkansas
|
242
|
|
13
|
Texas
|
214
|
|
14
|
Alaska
|
208
|
|
15
|
California
|
202
|
|
16
|
Missouri
|
194
|
|
17
|
Maryland
|
171
|
|
18
|
North Carolina
|
171
|
|
19
|
New Mexico
|
163
|
|
20
|
North Dakota
|
162
|
|
21
|
Puerto Rico
|
152
|
|
22
|
Virginia
|
144
|
|
23
|
Utah
|
143
|
|
24
|
Wisconsin
|
139
|
|
25
|
Minnesota
|
136
|
|
26
|
Iowa
|
133
|
|
27
|
Nebraska
|
124
|
|
28
|
Kentucky
|
121
|
|
29
|
Kansas
|
118
|
|
30
|
Indiana
|
115
|
|
31
|
Illinois
|
106
|
|
32
|
Washington
|
99
|
|
33
|
District of Columbia
|
98
|
|
34
|
Ohio
|
97
|
|
35
|
Colorado
|
94
|
|
36
|
Montana
|
91
|
|
37
|
Rhode Island
|
91
|
|
38
|
South Dakota
|
91
|
|
39
|
Oregon
|
75
|
|
40
|
Delaware
|
69
|
|
41
|
Michigan
|
69
|
|
42
|
Pennsylvania
|
69
|
|
43
|
West Virginia
|
66
|
|
44
|
Wyoming
|
66
|
|
45
|
New Jersey
|
55
|
|
46
|
Massachusetts
|
45
|
|
47
|
Hawaii
|
38
|
|
48
|
New York
|
32
|
|
49
|
Connecticut
|
19
|
|
50
|
Maine
|
18
|
|
51
|
New Hampshire
|
16
|
|
52
|
Vermont
|
9
|

Total deaths
Table of total deaths per million residents (all 50 states)
|
Ranking
|
State
|
Deaths Per Million
|
|
1
|
New Jersey
|
1,779
|
|
2
|
New York
|
1,661
|
|
3
|
Connecticut
|
1,239
|
|
4
|
Massachusetts
|
1,238
|
|
5
|
Rhode Island
|
947
|
|
6
|
District of Columbia
|
824
|
|
7
|
Louisiana
|
814
|
|
8
|
Michigan
|
641
|
|
9
|
Illinois
|
601
|
|
10
|
Delaware
|
594
|
|
11
|
Maryland
|
570
|
|
12
|
Pennsylvania
|
560
|
|
13
|
Mississippi
|
504
|
|
14
|
Arizona
|
456
|
|
15
|
Indiana
|
431
|
|
16
|
Georgia
|
323
|
|
17
|
Colorado
|
312
|
|
18
|
Alabama
|
304
|
|
19
|
New Hampshire
|
300
|
|
20
|
New Mexico
|
295
|
|
21
|
South Carolina
|
292
|
|
22
|
Minnesota
|
286
|
|
23
|
Ohio
|
286
|
|
24
|
Florida
|
276
|
|
25
|
Iowa
|
264
|
|
26
|
Virginia
|
243
|
|
27
|
Nevada
|
239
|
|
28
|
California
|
216
|
|
29
|
Texas
|
216
|
|
30
|
Washington
|
211
|
|
31
|
Missouri
|
202
|
|
32
|
North Carolina
|
173
|
|
33
|
Nebraska
|
166
|
|
34
|
Kentucky
|
162
|
|
35
|
Wisconsin
|
155
|
|
36
|
Tennessee
|
141
|
|
37
|
South Dakota
|
139
|
|
38
|
Arkansas
|
135
|
|
39
|
North Dakota
|
135
|
|
40
|
Oklahoma
|
125
|
|
41
|
Kansas
|
116
|
|
42
|
Vermont
|
89
|
|
43
|
Idaho
|
88
|
|
44
|
Maine
|
88
|
|
45
|
Utah
|
88
|
|
46
|
Oregon
|
68
|
|
47
|
Puerto Rico
|
62
|
|
48
|
West Virginia
|
59
|
|
49
|
Montana
|
43
|
|
50
|
Wyoming
|
43
|
|
51
|
Alaska
|
25
|
|
52
|
Hawaii
|
17
|

New deaths
Table of new deaths per million residents: rolling 3-day average (all 50 states)
|
Ranking
|
State
|
New Deaths Per Million
|
|
1
|
Texas
|
16
|
|
2
|
Arizona
|
7
|
|
3
|
South Carolina
|
7
|
|
4
|
Louisiana
|
5
|
|
5
|
Florida
|
4
|
|
6
|
Mississippi
|
4
|
|
7
|
Alabama
|
3
|
|
8
|
Georgia
|
2
|
|
9
|
Idaho
|
2
|
|
10
|
New Mexico
|
2
|
|
11
|
Arkansas
|
1
|
|
12
|
California
|
1
|
|
13
|
Illinois
|
1
|
|
14
|
Indiana
|
1
|
|
15
|
Iowa
|
1
|
|
16
|
Maryland
|
1
|
|
17
|
Massachusetts
|
1
|
|
18
|
Missouri
|
1
|
|
19
|
Nevada
|
1
|
|
20
|
New Jersey
|
1
|
|
21
|
North Carolina
|
1
|
|
22
|
Ohio
|
1
|
|
23
|
Puerto Rico
|
1
|
|
24
|
Tennessee
|
1
|
|
25
|
Wisconsin
|
1
|
|
26
|
Alaska
|
0
|
|
27
|
Colorado
|
0
|
|
28
|
Connecticut
|
0
|
|
29
|
Delaware
|
0
|
|
30
|
District of Columbia
|
0
|
|
31
|
Hawaii
|
0
|
|
32
|
Kansas
|
0
|
|
33
|
Kentucky
|
0
|
|
34
|
Maine
|
0
|
|
35
|
Michigan
|
0
|
|
36
|
Minnesota
|
0
|
|
37
|
Montana
|
0
|
|
38
|
Nebraska
|
0
|
|
39
|
New Hampshire
|
0
|
|
40
|
New York
|
0
|
|
41
|
North Dakota
|
0
|
|
42
|
Oklahoma
|
0
|
|
43
|
Oregon
|
0
|
|
44
|
Pennsylvania
|
0
|
|
45
|
Rhode Island
|
0
|
|
46
|
South Dakota
|
0
|
|
47
|
Utah
|
0
|
|
48
|
Vermont
|
0
|
|
49
|
Virginia
|
0
|
|
50
|
Washington
|
0
|
|
51
|
West Virginia
|
0
|
|
52
|
Wyoming
|
0
|

Counties
- This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
- Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
- In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.
Confirmed cases
Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
|
County
|
State
|
Cases Per Million
|
Raw Ranking
|
Percentile
|
|
Trousdale
|
Tennessee
|
138,337
|
1
|
99
|
|
Lake
|
Tennessee
|
102,052
|
2
|
99
|
|
Lee
|
Arkansas
|
98,905
|
3
|
99
|
|
Dakota
|
Nebraska
|
94,377
|
4
|
99
|
|
Buena Vista
|
Iowa
|
90,520
|
5
|
99
|
|
Davidson
|
Tennessee
|
29,034
|
112
|
96
|
|
Richland
|
South Carolina
|
17,058
|
386
|
87
|
|
Orange
|
California
|
10,910
|
816
|
74
|
|
York
|
South Carolina
|
10,172
|
890
|
71
|
|
Pierce
|
Washington
|
5,293
|
1634
|
47
|
Our county percentiles over time 
Deaths
Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
|
County
|
State
|
Deaths Per Million
|
Raw Ranking
|
Percentile
|
|
Hancock
|
Georgia
|
4,020
|
1
|
99
|
|
Randolph
|
Georgia
|
3,836
|
2
|
99
|
|
Terrell
|
Georgia
|
3,399
|
3
|
99
|
|
Early
|
Georgia
|
3,042
|
4
|
99
|
|
McKinley
|
New Mexico
|
3,013
|
5
|
99
|
|
Richland
|
South Carolina
|
305
|
650
|
79
|
|
Davidson
|
Tennessee
|
271
|
723
|
76
|
|
Orange
|
California
|
178
|
1001
|
68
|
|
Pierce
|
Washington
|
146
|
1136
|
63
|
|
York
|
South Carolina
|
85
|
1490
|
52
|
Our county percentiles over time 
Raw counts
- This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
- Total confirmed cases: This is the cumulative total of cases reported.
- New confirmed cases: This is the number of new cases reported on each respective date.
- For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
- Total deaths: This is the cumulative total of deaths reported.
- New deaths: This is the number of new deaths reported on each respective date.
- For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.
Total confirmed cases
U.S.

New confirmed cases
U.S.

Total deaths
U.S.

New deaths
U.S.

Stay-at-home comparisons
- This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
- The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
- So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
- Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
- As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
- The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
- I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.

